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Guseo, Renato - Guidolin, Mariangela (2009) Market potential dynamics in innovation diffusion: modelling the synergy between two driving forces. [Working Paper] WORKING PAPER SERIES, 10/2009 . , PADOVA (Inedito)

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Abstract (inglese)

The presence of a slowdown in new products' life cycle has recently received notable attention from many innovation diffusion scholars, who have tried to explain and model it on a typical dual-market hypothesis (early market-main market). In this paper we propose an alternative explanation for the slowdown pattern, based on the co-evolutionary model by Guseo and Guidolin, where diffusion results from the synergy between two driving forces: communication and adoption. We test the model on the sales data of six pharmaceutical drugs presenting a slowdown in their life cycle and observe that this is always identified almost perfectly by the model. A deeper analysis of the synergistic interaction between communication and adoption, based on the likelihood ratio order and on the usual stochastic order, shows that location indexes of each component (communication and adoption), such as mode, median and mean, can inform which of the two had a driving role in early diffusion. Contrary to the general expectation, according to which communication should precede adoptions, our findings show that in two cases adoptions were the main driver in early life cycle. We argue that this different behaviour may be due to the nature of the drug considered; new drugs developed for severe pathologies will be likely to have an accumulated demand at the time of launch, while drugs for minor ailments will present a normal behaviour, "first communication, then
adoption".


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Tipo di EPrint:Working Paper
Anno di Pubblicazione:25 Maggio 2009
Parole chiave (italiano / inglese):Co-evolutionary diffusion process, Dual-effect market, Communication network, Slowdown, Saddle, Chasm, New drugs, Likelihood ratio order.
Settori scientifico-disciplinari MIUR:Area 13 - Scienze economiche e statistiche > SECS-S/01 Statistica
Struttura di riferimento:Dipartimenti > Dipartimento di Scienze Statistiche
Codice ID:7148
Depositato il:09 Ott 2014 10:44
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